Ovarian cancer is a heterogeneous disease of low prevalence but poor survival. According to the World Health Organization (WHO) statistics in 2012, worldwide there were estimated to be 239 000 new ovarian cancer cases, representing 4% of all cancers in women. According to the statistics 152 000 deaths were caused by ovarian cancer in 2012. Ovarian cancer is the eighth most frequent cause of cancer death among women, and major proportion of new ovarian cancers occur in countries with high or very high levels of human development. The incidence rates are highest in Northern and Eastern Europe, North America and Oceania, and tend to be relatively low in Africa and much of Asia. However, during the 1990s and 2000s the incidence rate e.g. in China increased dramatically. (World Health Organization World Cancer Report 2014). The most common ovarian cancers are ovarian carcinomas, which include five main subtypes, and of those the high-grade serous carcinoma is the most common one (accounts approximately 70% of the cases). Early diagnosis is critical for the survival of the patient, as e.g. for the stage I patients the 5-year survival rate is around 90%, whereas for the stage IV patients it is only around 20%. However, the diagnosis of ovarian cancer is difficult, and the disease tends to cause symptoms for the patients only when advanced to later stages, and, in addition, the symptoms mimic often those of other diseases. Therefore new diagnostic tools that could detect ovarian cancer already in the early stages would be essential for successful treatment of ovarian cancer patients.
Previous methods to detect ovarian cancer have relied on protein biomarker analyses and imaging methods. The main diagnostic methods for ovarian cancer at the moment include pelvic examination, CA-125 blood test and transvaginal ultrasound. CA-125 and HE4 are the only two biomarkers US FDA approved for monitoring disease recurrence or progression, but not for screening. The multivariate index assay, OVA1, consisting of several protein biomarkers has been FDA approved for triage of pelvic masses since 2009. (Nguyen et al., Women's Health, 2013, 9(2), 171-187). CA-125 has been reported to be a prognostic factor for overall and progression free survival in ovarian cancer, but also studies showing contradictory results exist. CA-125 levels are raised in approximately 90% of patients with advanced epithelial ovarian cancer, but only in 50% of patients with stage I disease (Gupta & Lis, Journal of Ovarian Cancer, 2009, 2:13). Thus, the golden standard, CA-125 is relatively good in detecting patients with advanced disease, but it is lacking sensitivity in other patients and its role in predicting survival is somewhat controversial.
Small molecules, including metabolites and lipids are attempting diagnostic tools as compared to protein biomarkers, since they directly reflect the changes in metabolism, which are known to occur already early in the tumor initiation and progression. Small changes in the gene expression or protein levels of specific pathways may result in large changes in the small molecule metabolite and lipid concentrations, as their levels can be considered to be an amplified output of the activity of the biological pathways. Despite some attempts to find small molecule markers for ovarian cancer, previous disclosures have failed to provide simple and reliable small molecule ovarian cancer biomarkers from blood serum that would have been taken into clinical practice. WO2009151967 describes a large panel of metabolic biomarker candidates and machine learning classification algorithms for ovarian cancer diagnostics. WO2012038525A1 describes a large panel of phospholipids as biomarkers for various cancers. WO2013016700 describes the use of classification algorithms to produce predictive models for epithelial ovarian cancer using data from mass spectrometry (MS) or nuclear magnetic resonance (NMR). NMR technique has been applied also in other disclosures describing potential biomarker candidates for ovarian cancer, such as WO2011041892 and US2005170441. However, the limitation of the previous investigations is in general the description of large panel of biomarkers, which could have not been narrowed down using other information from the cancer patients, such as prognosis or investigations on correlation of the biomarker levels between serum and tumor tissue. Furthermore, there are no disclosures showing how the information of single metabolites or metabolite combinations together with protein markers could be combined in order to give more accurate diagnostic and prognostic methods for ovarian cancer patients. Thus, focused small molecule biomarker panels would be extremely useful for better ovarian cancer diagnostics.